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Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: J. Borovec <jirka.borovec@seznam.cz>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
2020-03-20 20:49:01 +01:00

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Training Tricks
================
Lightning implements various tricks to help during training
Accumulate gradients
-------------------------------------
Accumulated gradients runs K small batches of size N before doing a backwards pass.
The effect is a large effective batch size of size KxN.
.. seealso:: :class:`~pytorch_lightning.trainer.trainer.Trainer`
.. code-block:: python
# DEFAULT (ie: no accumulated grads)
trainer = Trainer(accumulate_grad_batches=1)
Gradient Clipping
-------------------------------------
Gradient clipping may be enabled to avoid exploding gradients. Specifically, this will `clip the gradient
norm <https://pytorch.org/docs/stable/nn.html#torch.nn.utils.clip_grad_norm_>`_ computed over all model parameters together.
.. seealso:: :class:`~pytorch_lightning.trainer.trainer.Trainer`
.. code-block:: python
# DEFAULT (ie: don't clip)
trainer = Trainer(gradient_clip_val=0)
# clip gradients with norm above 0.5
trainer = Trainer(gradient_clip_val=0.5)